At present, wireless communication is primarily used in cellular networks, in the radio local loop, and in radio broadcasting. The exponential growth of wireless communication and the scarcity of radio-frequency wavelengths makes it crucial to optimize the RF spectrum resource.
The transmission channel is usually considered as a sum of diracs, i.e. as the same signal repeated and superposed on itself several times, with a plurality of variable offsets. The processing by the receiver usually includes tuned filtering followed by correlation. After tuned filtering, a correlation is effected with the conjugate of the code modulating the symbol for each delay associated with one of the selected paths. The correlation result is multiplied by the conjugate of the estimate of the amplitude of the path, and the various results are finally summed.
In radio transmission, the transmitted signal can take different paths between the sender and the receiver. Thus the receiver may receive different delayed and phase-shifted replicas of the transmitted signal that add constructively and/or destructively. With some kinds of destructive addition, the phenomenon known as total fading can occur. Diversity techniques are of some efficacy in the fight against the phenomena of serious fading. Those diversity techniques are classified into various categories: space diversity, polarization diversity, frequency diversity, time diversity, multipath diversity.
A typical rake receiver takes multipath diversity into account. Such a receiver synchronizes all the paths and then combines them by means of a maximum radio combining (MRC) process. That type of receiver has been the subject of numerous enhancements since the introduction of spread spectrum communication systems such as UMTS and CDMA 2000.
At the combination stage, the processing by the receiver may include a selection process. At present, the selection process can be a semidynamic selection process (GSC algorithm), a threshold selection process, or a static selection process (MRC algorithm).
Adaptive GSC algorithms achieve the best compromise between complexity and bit error rates. They have an output threshold, generally a target signal-to-noise ratio (SNR), for determining the number of fingers of the rake to be taken into account. Provided that the output of the rake receiver is not above this threshold, the receiver increases the number of fingers to be taken into account and thus the number of paths to be combined. These algorithms include:                The Kim, Ha, and Reed algorithm described in the document by SuK Won Kim, Dong S. Ha, and J. H. Reed “Minimum Selection GSC and Adaptive Low-Power Rake Combining Scheme”, IEEE, 2003. The objective of that algorithm is to guarantee a target bit error rate (BER) at the output of the receiver; and        The Alouini and Yang algorithm described in the document by Mohamed-Slim Alouini and Hong-Chuan Yang “MRC Diversity with an Output Threshold”, IEEE ICC', 2004. That algorithm uses the same principle as the preceding algorithm, from which it differs in that it adds paths until the SNR of the recombined signal is equal to or greater than a predetermined target SNR.        
Those algorithms are disadvantageous when the SNR obtained after combining all the paths remains below the target SNR. To guarantee an instantaneous output SNR, those algorithms select all the paths even though paths with a low SNR can have a negative effect on the SNR obtained after combination.